Generic farm management apps track livestock; they were not built for poultry — and the difference shows up exactly where poultry decisions live: weight against a strain-specific curve, feed conversion measured against age, mortality patterns that mean something in a broiler house, and settlement records that have to reconcile with an integrator's performance sheet. The migration question is not whether the generic app "can" hold poultry data — a generic table can hold anything — but whether its reports and record types produce the poultry-specific numbers your operation runs on. This page covers how to evaluate that gap honestly and what the migration involves when the answer is that the gap is real.
The Poultry-Specific Check
| What Poultry Runs On | Generic-App Question to Answer | PoultryLog™'s Version |
|---|---|---|
| Weight against a breeder curve | Does the system chart weights against strain- and age-specific targets, or only store the numbers? | Growth charts against published Cobb 500 and Ross 308 curves — the growth chart guide covers the reference data |
| Feed conversion by age | Does it compute FCR from logged feed and weights, per flock? | FCR computed from the logged data — the FCR guide covers the benchmarks |
| Mortality patterns | Are mortality entries per flock and house with time, or a single running count? | Per-house entries with time-of-day — the cause-signature table shows why the structure matters |
| Settlement reconciliation | Can integrator performance values be recorded per flock beside your own logs? | Performance records tied to flock and source document — the settlement comparison guide covers the reconciliation |
| Cost per pound produced | Do expenses attribute per flock and compute against pounds sold? | Per-flock expense attribution with cost-per-pound outputs — the break-even guide covers the number |
The Staged Cutover Method
- Run the check above on the app you have before deciding anything. If the generic app answers every row, the migration may not be necessary — good. If it answers none, that is the honest basis for switching, not a competitor's marketing.
- Start at a clean boundary — new flock or new month. Mid-flock migrations force dual entry; the boundary removes it. The paper migration guide covers the principle.
- Move finance history, seed the active flock. Expense and income rows import through the finance CSV import (Excel-compatible templates, Growth plan and above); current flock state is entered directly. The budget template runs on that data.
- Re-point the reports that carried decisions. Name them explicitly — which figures, which periods — and verify the first month's output matches what the generic app's reports gave you.
- Verify at the first settlement comparison. The first settlement checked against the new record set is the proof: the comparison method runs from there.
What the Migration Changes
The record set stops being generic storage and starts being poultry decision support: growth against curve, conversion against age, mortality with structure, settlement beside your own logs, and cost per pound computed per flock. The software guide covers the full evaluation; the digital records guide covers what the record set needs to contain regardless of which system holds it.
Tracking in Poultry Log™
PoultryLog™'s logs, charts, and finance records are built for the rows in the table above — the poultry-specific numbers, computed from data entered in the barn. The profitability dashboard carries the margin trend; the cost per bird guide covers the per-unit metric.
- 2026-10-06: Comprehensive rewrite as an honest evaluation method — poultry-specific capability check, boundary-based cutover, and no competitor feature claims — replacing the earlier version with fabricated first-person claims.
- Earlier version: first-person narrative about switching from a generic farm app.